Crowdsourcing, conceptually, can be defined as a distributed work process in which tasks are outsourced to participants (the crowd) who contribute based on their skills or opportunities, collaboratively solving tasks to produce a common result. This model can be found across various domains, from economics and engineering to technology and the digital, data-driven fabric of modern society. The relevance of crowdsourcing extends to the security sector, which, in the 21st century’s era of hybrid conflicts, is increasingly focused on maximising the potential of cyberspace; in particular, fields such as information warfare, which includes influencing members of society, deceiving adversaries through disinformation, and conducting cyberspace-related intelligence and information gathering. The phenomenon is now present on social platforms, widely used by society. On the one hand, they create an abundance of openly available information; on the other, they serve as platforms for deception and the dissemination of misinformation.

Crowdsourcing is used across a wide range of research areas and is evident in our everyday lives (Castillo, 2013; Gupta and Brooks, 2013, p. 27). Participants contribute their data, knowledge, or resources, such as financial support (e.g. crowdfunding), to the creation, improvement, or refinement of a collective “outcome.” It is present in information and communications technology (ICT), including the crowdsourcing of the Internet of things (Anopa et al., 2023) as well as in business and marketing. It is also increasingly significant in the social sciences, where it has driven specific directions of innovation, such as geo-crowdsourcing and crowdfunding (Brovelli et al., 2019, pp. 838–863; Demiray et al., 2019, pp. 115–151).

However, “crowdsourcing” as a model is not a phenomenon unique to the 21st century. From a scientific perspective, crowdsourcing refers to the outsourcing of parts of work processes and human resources in a distributed manner (Stottlemyre, 2015). It involves engaging crowds as distributed resources to perform various “subtasks,” which today, thanks to online space and communities, has evolved into a powerful distributed problem-solving capability (Brabham, 2008, p. 76). The logical progression of this development is to obtain solutions or insights from actors in cyberspace who can provide relevant information, whether through professional expertise or their presence in specific contexts. The term “crowdsourcing” is often attributed to Jeff Howe (2006), who introduced it from a business perspective in a 2006 article. Today, however, distributed work based on cooperation is prevalent across various aspects of life, as numerous technological and infocommunication solutions are built upon shared resources. The rise of crowdsourcing has been propelled by the accessibility of infocommunication tools at the individual level, which has expanded the spatial boundaries of the information we can access and share. These tools essentially act as “sensors” of our daily lives.

The opinions and information shared on various social platforms can be particularly valuable in critical security situations, as they often provide more accurate and up-to-date information than traditional sources. However, beyond these ideal scenarios, questions may arise about the value and reliability of the information shared. What is undeniable is that during such periods (e.g. natural disasters or conflicts), there is an increased demand for accurate and credible information from both members of society and public organisations responsible for security. In this context, cyberspace-based crowdsourcing solutions can play a significant role in supporting the work of agencies responsible for ensuring security.

Based on examples from the international literature, the crowdsourcing approach to national security demonstrates the collective power of communities, whether in information gathering, analysis, or forecasting. In this context, gaining a deeper understanding of the potential applications of the method and continuously seeking ways to further develop it for security purposes is essential. The aim of this paper is to contribute to the scientific discourse on applying crowdsourcing to (national) security by highlighting some of its main directions, as identified in the literature and current international examples. The paper categorises the topic into four key areas: information gathering, cybersecurity, expert analysis, and security foresight. It examines the specifics of these application directions as well as the advantages and limitations of the method.

A key element of this research is the concept of “collective intelligence”, which refers to the shared abilities and knowledge of group members. A fundamental aspect of collective intelligence is the ability and willingness to cooperate, where participants work together towards a common goal and share tasks among themselves. This concept is demonstrated in numerous international examples, which serve as a basis for this study. As an inductive research method, this paper examines the topic by drawing on case studies from the literature and incorporating the findings of other authors in the context of security-related applications. While crowdsourcing is now highly diverse, much of it is not directly related to security. Therefore, during the literature review, document analysis, and selection of examples, a focus was placed on identifying examples that are central and illustrative for security-related applications (e.g. Papapesios et al., 2019). The reviewed sources and examples provided the basis for identifying key characteristics and elements of crowdsourcing in security contexts as well as for outlining its main application directions. The choice of research method reflects the observation that crowdsourcing, as a theory, is often intertwined with security-related activities. This study seeks to explore how the method can be applied within the paradigm of security, rather than treating it as a distinct, clearly delineated category.

Due to a lack of available data, this study did not aim to explore the inner workings and characteristics of crowdsourcing systems. Instead, it aimed to identify specificities along the lines of the categorisation of security-related applications. At the same time, given the broad interpretability of security, it is not possible to draw sharp distinctions between the categories identified in the study. However, the examples examined provide valuable illustrations of how crowdsourcing is applied in these security-related contexts. It is hoped that identifying the main application categories and outlining the advantages and disadvantages of the method will be beneficial for those considering crowdsourcing solutions. Additionally, the study aims to offer ideas that could facilitate the further development and application of crowdsourcing in security-related fields.

This research aligns with the growing research direction in applying crowdsourcing methods to security contexts (Halder, 2014; Hui, 2015; Markowsky, 2013). The global information environment, characterised by the availability of vast amounts of data in various formats and platforms, opens new perspectives for security applications. For instance, during a security incident, the challenge of identifying and selecting relevant information of value becomes significant. This increases the importance of sources that can enable security organisations to act more accurately and quickly. From this perspective, crowdsourcing views crowd members as distributed resources whose significance lies in their skills or geographic location. In critical security incidents, identifying the fastest and most accurate source of information becomes crucial. On the one hand, individuals in the affected geographic area may possess relevant information, and available tools can facilitate the transmission of that data. However, the accuracy and authenticity of the data cannot be guaranteed, whether due to accidental errors or intentional deception. Therefore, the advantages and disadvantages of crowdsourcing as a method must be considered carefully.

In this regard, as a methodological element, it is important to examine the distinct components of crowdsourcing (the crowd, the crowdsourcer, the crowd-sourced task, and the crowdsourcing platform; Hosseini et al., 2014, pp. 1–12). Additionally, consideration must be given to both advantages and disadvantages of crowdsourcing, including data reliability, as well as the motivation and willingness of participants to participate.

The conflicts of recent years have increasingly valued crowdsourcing solutions for security purposes. This trend reveals an increasingly complex picture, encompassing areas such as intelligence, analysis, forecasting, cybersecurity, and cyberattacks. One key factor driving this development is the involvement of civil society actors in modern armed conflicts. In today’s conflicts, alongside traditional military forces, civilian participants are also engaged—often through invisible networks—on both defending and attacking sides. These actors contribute to the events by providing information and support within cyberspace.

In a national security context, a key objective is to obtain the most accurate and up-to-date understanding of a given event. Achieving this requires human resources capable of contributing their skills, expertise, and information to piece together a more complete picture from mosaic-like elements.

Aligned with these objectives, numerous international examples demonstrate the use of crowdsourcing for security and national security purposes. These efforts use the unique characteristics of the online space to their advantage, including:

the actors of the information environment engaged in the given task (either information collection or analysis), which can be used to enhance capabilities;

On the other side of the coin, crowdsourcing also presents challenges and disadvantages, making it unsuitable as a “one-size-fits-all” solution:

Authenticity and accuracy of data provided by participants as well as the underlying motivations for their contributions.

Based on the international examples reviewed, this study has grouped the main applications of crowdsourcing for security purposes into four clusters and seeks to highlight the relevance of the topic through their main characteristics (Figure 1). The clusters are not rigidly defined, and their boundaries often overlap.

The examined examples suggest that the crowdsourcing approach has potential applications in various aspects of security and national security thinking. However, both limitations and advantages of the method must be considered (see Figure 2). While national security thinking is often “closed” in many areas, critical events, such as terrorist attacks or open military conflicts, create a need for information flows that extend to society. These information needs are particularly apparent in the areas where communication and collaboration with broader social groups can support security interests. Examples include assistance during natural and man-made disasters, law enforcement efforts, or the dissemination of accurate information during armed conflicts (Moghadas et al., 2023; Papapesios et al., 2019).

Regarding the advantages of the crowdsourcing method, several general benefits can be identified. These include a reduction in reaction time, an increase in the volume of information (and the anticipated accuracy), and economic, social, and human advantages. Other authors highlight the power of the crowd, emphasising the utilisation of human resources and expertise, the potential for discreet work, cost savings, and even fostering innovation (Hui, 2015, p. 5). However, crowdsourcing is not a universal solution for addressing security issues. Applications for security purposes raise specific questions, such as whether participant anonymity is necessary or how to ensure data authenticity and accuracy (Ilbiz and Kaunert, 2023). By definition, it depends on the purpose of the crowdsourcing application, whether it is necessary to ensure the anonymity of the individual contributing by solving partial tasks and providing partial information as part of the “anonymous” crowd. In one case, for example, we can think of using a route planner, where we contribute with our efforts to determine the amount of traffic, while in another case we want to contribute to increasing security by handing over digital evidence (“anonymous reporting”).

Another critical aspect is that many security-related applications are connected to public organisations and tasks, which often raises concerns about personal data protection and privacy. These issues can significantly influence public motivation and willingness to participate (Kumar and Faisal, 2024). For example, the COVID-tracking applications faced resistance due to fears about potential privacy violations, which acted as a restraining force (Németh and Magyar, 2021). Similarly, the open use of social media platforms for security purposes, as seen during the Russian-Ukrainian war, has highlighted similar concerns regarding data privacy and user anonymity.

Social platforms offer a viable medium for expanding crowdsourcing initiatives. However, in security-related topics, it is crucial to ensure both authenticity of the information and safety (including anonymity) of the participants. Due to their openness, such platforms are particularly vulnerable to influence, manipulation, and the dissemination of disinformation, which can undermine the authenticity of “community” knowledge. Community-sourced data also raises concerns about accuracy and credibility. While inaccuracies may result from innocent errors, they can also stem from deliberate actions, such as intentional deception.

The phenomenon of data poisoning, where malicious participants deliberately contaminate data collection with misleading information, poses a significant challenge, particularly in security applications. This contamination can negatively impact the accuracy of aggregated results, potentially leading to erroneous conclusions and decisions (Tahmasebian et al., 2020). In security-related contexts, where the data collected may directly influence societal safety, the intentional manipulation of information is especially concerning. Such malicious and intentional actions can lead to erroneous conclusions and decisions and can undermine trust in these applications. In today’s world, where data analysis and evaluation are increasingly reliant on artificial intelligence solutions, the importance of “authentic” data is crucial, as inaccurate data can distort the entire analysis process.

As a potential solution, double-checking smaller and refined datasets that emerge as valuable during the crowdsourcing process (e.g. through expert validation) can help mitigate inaccuracies. Additionally, leveraging the collective effect of mass confirmation (where multiple participants validate the same information) can neutralise the impact of inaccurate data. While this solution is more feasible in crowdsourcing intelligence applications, where data can be verified against existing facts or expert analysis, it presents a challenge in crowdsourcing forecasting. In forecasting scenarios, the accuracy of predictions can only be verified retrospectively after the predicted event has occurred.

Crowdsourcing has become an integral yet often invisible part of our daily lives. Its relevance to security has been amplified by several factors. First, the evolution of information technology (IT) tools and environments has expanded the potential for crowdsourcing applications. Second, security authorities have recognised the value of mobile communication tools, which are essential for individuals to share information globally. These tools can generate relevant security-related information, which makes them a valuable asset for public authorities. Mobile devices can serve as a vital data feed. However, when designing and implementing such targeted applications, there are also a number of other aspects to consider.

The study identified four areas of application (namely information collection, expert use, cybersecurity, and security forecasting) where the crowdsourcing model is already demonstrating practical relevance to national security. These areas provide valuable examples and insights that can help shape the future use of crowdsourcing and contribute to the broader discourse on the subject.

The common elements underlying these types of applications include:

the necessity for involvement and voluntary participation,

However, alongside the advantages of the method outlined in the study, there are several limitations that must be acknowledged. These challenges may stem from the participants themselves (e.g. the need for anonymisation, the reliability and credibility of data contributors) or from the datasets generated through their participation (e.g. data accuracy, credibility, and the security of the systems). It is therefore essential for developers of crowdsourcing-based applications to be mindful of these constraints and to address them during the design process. Ensuring robust safeguards and mechanisms to mitigate these challenges is critical to the effective applicability of the method. Failure to do so could result in cumulative community knowledge producing erroneous results.

What can be expected of the future? The nature of future security incidents and the associated open involvement of societal actors will undoubtedly shape the evolution of crowdsourcing security applications. The capacity to disseminate information through communication channels—whether in the context of ongoing conflicts, unforeseen natural or man-made disasters, or the complex domain of cybersecurity—will increasingly highlight the value of human involvement organised through crowdsourcing processes. Nevertheless, the role of civil society members as observers or external experts opens up numerous research avenues worthy of further exploration.